Power control in cognitive radio systems based on spectrum sensing side information

ABSTRACT

For cognitive radio systems, the transmit power of a cognitive radio device is controlled so that the cognitive, unlicensed radio device does not interfere with the use of a shared spectrum by a primary, licensed device. Controlling the transmit power includes determining a distance, or a function of the distance, between a primary transmitter of the primary device and the cognitive radio device based on sensing information from a spectrum sensing process. The maximum transmit power of the cognitive radio device is then dynamically controlled based on the distance, or the function of the distance, while considering a worst case scenario of an underlying cognitive radio model, to guarantee a quality of service requirement of the primary device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional applicationSer. No. 13/223,120, now U.S. Pat. No. 8,315,663 having issued on Nov.20, 2012, filed on Aug. 31, 2011, entitled “POWER CONTROL IN COGNITIVERADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION,” which is acontinuation of U.S. Non-Provisional application Ser. No. 12/099,886,now U.S. Pat. No. 8,041,380 having issued on Oct. 18, 2011, filed onApr. 9, 2008, entitled “POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASEDON SPECTRUM SENSING SIDE INFORMATION ,” which claims priority to U.S.Provisional Application Ser. No. 60/914,140, filed on Apr. 26, 2007,entitled “POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUMSENSING SIDE INFORMATION,” the entireties of which are incorporatedherein by reference.

TECHNICAL FIELD

The subject disclosure relates to power control based on spectrumsensing side information in cognitive radio systems.

BACKGROUND

By way of brief background, cognitive radio is a paradigm for wirelesscommunication in which either a network or a wireless node changes itstransmission or reception parameters to communicate efficiently withoutinterfering with licensed users. This alteration of parameters is basedon actively monitoring several factors in the external and internalradio environment, such as radio frequency spectrum, user behavior andnetwork state.

In cognitive radio systems, the unlicensed (secondary) users can use thelicensed spectrum as long as the licensed (primary) user is absent atsome particular time slot and some specific geographic location.However, when the primary user reappears (i.e., comes back and ispresent again), ideally, the secondary users should vacate the spectruminstantly to avoid interference with the primary user.

The explosive growth in wireless services over the past several yearsillustrates the huge and growing demand of the business community,consumers and the government for wireless communications. With thisgrowth of communication applications, the spectrum has become even morecongested. Even though the Federal Communications Commission (FCC) hasexpanded some spectral bands, these frequency bands are exclusivelyassigned to specific users or service providers. Such expansion does notnecessarily guarantee that the bands are being used most efficiently allthe time.

In this regard, it has been shown that most of the radio frequencyspectrum is vastly under-utilized. For example, cellular network bandsare overloaded in most parts of the world, but amateur radio or pagingfrequencies are not. Moreover, those rarely used frequency bands areassigned to specific services that cannot be accessed by unlicensedusers, even where transmissions of the unlicensed users will notintroduce any interference to the licensed service.

To deal with the conflicts between spectrum congestion and spectrumunder-utilization, cognitive radio has been recently proposed as a smartand agile technology, which allows non-legitimate users to utilizelicensed bands opportunistically. By detecting particular spectrum“holes” and jumping into them rapidly to meet demand for spectrum,cognitive radio can improve the spectrum utilization significantly. Toguarantee a high spectrum efficiency while avoiding interference tolicensed users, cognitive radio should be able to adapt to spectrumconditions flexibly. Hence, improvements for cognitive radio are desiredin the areas of spectrum sensing, dynamic frequency selection andtransmit power control.

One of the most challenging problems of cognitive radio is theinterference that occurs when a cognitive radio accesses a licensedband, but fails to notice the presence of the licensed user. To addressthis problem, cognitive radios should be designed to co-exist with thelicensed user without creating harmful interference. Some conventionaltechniques that have been proposed to mitigate interference by theunlicensed user in cognitive radio systems include: (1) an orthogonalfrequency division multiplexing (OFDM) approach proposed to avoid theinterference by leaving a set of subchannels unused, (2) a transformdomain communication system (TDCS) approach proposed to mitigate theinterference by not placing the waveform energy at corrupted spectrallocations and (3) a power control approach proposed to allow cognitiveradios to adjust their transmit powers in order to guarantee quality ofservice (QoS) to the primary system based on a measurement of localsignal to noise ratio (SNR) of the primary signal.

To avoid interference to licensed users, however, the transmit power ofcognitive radios should be limited based on the locations of thelicensed users. The third approach above begins from the assumption thatcognitive radios have no way of knowing these locations of the licensedusers, and then proposes the use of SNR as a proxy measurement, however,if the primary receiver is a TV antenna on a roof, it might measure aSNR of 0 dB at one location, while a cognitive radio on the ground atthe same location might measure −10 dB, and thus SNR is a weak proxythat does not appear to directly correlate to the locations of thelicensed users.

In this regard, it is difficult to locate the licensed users for thecognitive radio in practice because the channels between the cognitiveradio and the licensed users are usually unknown. Furthermore, theenvironment where the system is in operation may have a large delayspread and, hence, the channel model between cognitive radios andprimary users is complicated by fading, shadowing and path loss effects.

In another conventional system, a local oscillator (LO) leakage power isexploited to try to locate the primary receivers. However, such anapproach is difficult to apply in practice because the approach requiresa sensor node mounted close to the primary receivers to detect the LOleakage power, which is not very practical.

Accordingly, improved systems and methods are desired for improvingpower control for cognitive radio systems that do not depend uponadditional structure, such as sensor nodes for detecting LO leakagepower, being added close to the primary receivers. Moreover, systems aredesired that control power of a cognitive radio based on a measurement,related to distance to licensed users, which is not inherently flawed aswith the third approach discussed above.

The above-described deficiencies of current designs are merely intendedto provide an overview of some of the problems of today's designs, andare not intended to be exhaustive. Other problems with the state of theart of cognitive radio and corresponding benefits of the invention maybecome further apparent upon review of the following description ofvarious non-limiting embodiments of the invention.

SUMMARY

A simplified summary is provided herein to help enable a basic orgeneral understanding of various aspects of exemplary, non-limitingembodiments that follow in the more detailed description and theaccompanying drawings. This summary is not intended, however, as anextensive or exhaustive overview. The sole purpose of this summary is topresent some concepts related to the various exemplary non-limitingembodiments in a simplified form as a prelude to the more detaileddescription that follows.

For cognitive radio systems, the transmit power of a cognitive radiodevice is controlled so that the cognitive, unlicensed radio device doesnot interfere with the use of a shared spectrum by a primary, licenseddevice. In exemplary, non-limiting embodiments, the power controlmethodology of the invention includes determining a distance, or afunction of the distance, between a primary transmitter of the primarydevice and the cognitive radio device based on sensing information froma spectrum sensing process. The maximum transmit power of the cognitiveradio device is then dynamically regulated based on the distance, or thefunction of the distance, while considering a worst case scenario of anunderlying cognitive radio model, to guarantee a quality of servicerequirement of the primary device.

BRIEF DESCRIPTION OF THE DRAWINGS

The various embodiments for the power control techniques based onspectrum sensing side information are further described with referenceto the accompanying drawings in which:

FIG. 1 illustrates a high-level block diagram of the power control basedon spectrum sensing side information;

FIG. 2 is a flowchart illustrating a first non-limiting method forperforming power control based on spectrum sensing side information;

FIG. 3 is a flowchart illustrating a second non-limiting method forperforming the power control based on spectrum sensing side information;

FIG. 4 is an exemplary, non-limiting block diagram showing a systemmodel for the power control techniques described herein;

FIGS. 5 and 6 illustrate exemplary graphical demonstrations of effectson a probability of missing in connection with spectrum sensing forcognitive radio;

FIGS. 7 and 8 illustrate exemplary graphical demonstrations inconnection with spectrum sensing for cognitive radio laying a foundationfor different mathematical relationships;

FIG. 9 is an illustrative graph showing results and benefits of thepower control based on side information of spectrum sensing techniques;

FIG. 10 is a flowchart illustrating a third non-limiting method forperforming power control based on spectrum sensing side information;

FIG. 11 is a block diagram representing an exemplary non-limitingnetworked environment;

FIG. 12 is a block diagram representing an exemplary non-limitingcomputing system or operating environment; and

FIG. 13 illustrates an overview of a network environment suitable fortransmission of data and service for the various embodiments describedherein.

DETAILED DESCRIPTION Overview

As mentioned in the background, cognitive radio has been recentlyproposed as a promising technology to improve spectrum utilizationefficiency by intelligently sensing and accessing some vacant bands,termed holes, of licensed users. In this regard, as described in thebackground, power control algorithms have been proposed to allowcognitive radios to adjust their transmit powers in order to guaranteeQoS of the licensed users. However, presently, it is difficult inpractice to locate licensed users with existing systems, and sointerference with licensed users can result. For instance, the SNRcharacteristic measured by at least one conventional system isunreliable, error-prone and not correlated properly with distance.

In consideration of these limitations on current power controltechniques, in accordance with various non-limiting embodiments,cognitive radios are allowed to operate in the presence of the licenseduser by controlling the transmit power of cognitive radios. In order tominimize the interference to the licensed user, the transmit power ofthe cognitive radio is controlled by using spectrum sensing sideinformation, guaranteeing QoS for licensed users in the presence ofunlicensed cognitive radios.

In various non-limiting embodiments, power control is provided forcognitive radio systems based on spectrum sensing side information inorder to mitigate the interference to the primary user due to thepresence of cognitive radios. In one embodiment, first, the shortestdistance between a licensed receiver and a cognitive radio is derivedfrom the spectrum sensing side information. Then, the transmit power ofthe cognitive radio is determined based on this shortest distance toguarantee a QoS for the licensed user. Because the worst case isconsidered in this approach where the cognitive radio is the closest tothe licensed user, the proposed power control approach can be applied tolicensed users in any location.

FIG. 1 is an exemplary, non-limiting block diagram generallyillustrating the power control techniques applied to an unlicensedcognitive radio 100 in order to maintain QoS requirement(s) 116 for alicensed primary user 110 when the cognitive radio 100 and the licenseduser 110 are both utilizing shared spectrum 120. As illustrated, primaryuser 110 includes a primary transmitter 112 and a primary receiver 114.As shown, cognitive radio 100 includes a transmitter 106, a powercontrol module 104 and a spectrum sensing component 102. In accordancewith the invention a distance d or a function of the distance d isdetermined by power control component 104 based on data determined byspectrum sensing component 102. The power of transmitter 106 is in turncontrolled by power control module 104 as function of the distance d. Byconsidering a worst case scenario for guaranteeing QoS requirements 116,power control module 104 allows cognitive radio 100 to share thespectrum 120 without interfering with the operation of the primary user110.

The methodology of the invention is further illustrated in the exemplarynon-limiting flow diagram of FIG. 2. At 200, the distance d between aprimary transmitter (licensed) and a cognitive radio (unlicensed) isdetermined based on spectrum sensing side information. Then, at 210, inaccordance with the processes described below, the transmit power of thecognitive radio is controlled based on the distance d in order toguarantee any QoS requirement(s) associated with the primary receiver.

As illustrated in the flow diagram of FIG. 3 in exemplary non-limitingdetail, at 300, the determination of the distance d may includecalculating the average probability of missing energy detection withrespect to determining the presence of the primary transmitter of theprimary user during spectrum sensing of the cognitive radio. Then, at310, based on the average probability of missing calculated at 300, thedistance d between the primary transmitter and the cognitive radio (or afunction based on the distance d, such as path loss due to the distanced) is determined. Then, at 320, the transmit power control of theinvention is implemented by calculating the maximum transmit power forthe cognitive radio as a function of the distance d (or the function,such as path loss) based on the distance d. As a result, the transmitpower of the cognitive radio guarantees acceptable QoS for the primaryreceiver.

In the below description, various aspects of a system model arepresented as a foundation for the various embodiments for implementingpower control using side information of spectrum sensing describedherein. Then, some non-limiting results are presented that demonstratethe efficacy of the invention. Then, some further background aboutcognitive radio systems is provided for some additional context relatingto cognitive radio systems, followed by some non-limiting operatingenvironments in which one or more aspects of the embodiments describedherein may be implemented.

System Models

As foundation for the various embodiments of the invention described inmore detail below, the invention considers a primary system (i.e.,licensed user), formed by a transmitter-receiver pair, co-existing witha secondary user (cognitive radio) in the same area. A system model ofinterest in accordance with the invention is illustrated in FIG. 4,wherein primary transmitter PTx, primary receiver PRx and cognitiveradio CR are depicted, respectively.

In the primary system, the primary transmitter PTx communicates with theprimary receiver PRx with a transmit power Q_(p). Some system parametersthat are shown in FIG. 4 are explained as follows. The circle around theprimary transmitter PTx with the radius R_(d) (m) represents thedecodable region within which the signal-to-noise ratio (SNR) ofdecodability occurs in the absence of interference to the primaryreceiver. The circle around the primary transmitter PTx with the radiusR_(p) (m) denotes the protection region within which the primaryreceiver PRx must be guaranteed successful reception even in thepresence of cognitive radio CR. Δ (dB) is the signal attenuation due tothe distance R_(d)·μ is the margin of protection in dB, which representshow much interference the primary system can tolerate above the noisefloor.

In the secondary system, cognitive radio CR optionally works in the samefrequency band as the primary system. Before accessing the channel,cognitive radio CR acts as a listener to detect from the receivedsignals whether the primary system is in operation. Let d (m) denote thedistance between the primary transmitter PTx and cognitive radio CR. Inpractice, it is difficult to obtain the value of d because the signalsfrom the primary transmitter PTx and the channel are both unknown tocognitive radio CR.

Another challenging issue is allowing cognitive radio CR to access thesame spectrum band where the primary user is operating. In such a case,cognitive radio CR may interfere with the primary system, thereby,degrading the QoS for the primary receiver. To reduce the interference,the transmit power Q_(c) of cognitive radio CR is limited based on thetolerable interference to primary receiver PRx which directly depends onthe distance between cognitive radio CR and primary receiver PRx.However, it is difficult for cognitive radio CR to locate primaryreceiver PRx, which can be at any location inside the protection region.

To address this problem, a worst case scenario is considered as a boundin accordance with the invention where primary receiver PRx is locatedon the crossing point between the boundary of the protection region andthe line from primary transmitter PTx to cognitive radio CR as shown inFIG. 4. By limiting the transmit power of the cognitive radio CR forthis worst case, acceptable QoS is maintained for the primary receiverPRx in operation at any location inside the protection region. In thiscase, it can be seen from FIG. 4 that the transmit power of cognitiveradio CR, which is allowed to inflict tolerable interference on theprimary receiver, depends on the SNR loss (μ+ψ) in dB. It is also notedthat the SNR loss due to the distance d is given by η=ψ+Δ (dB). Then,the transmit power control problem is converted to the problem ofevaluating the SNR loss η due to d for a given μ and Δ.

The channel between any two terminals in FIG. 4 is assumed to experienceflat Rayleigh fading and path loss. The propagation power attenuation ischaracterized by Q(r)=r^(−α), where r represents the distance and αdenotes the power loss exponent (i.e., a constant typically in the rangeof 2˜6). Herein, α=2 is used which corresponds to a free-spaceattenuation parameter.

Power Control Based on Spectrum Sensing Side Information

As mentioned, in accordance with the invention, a power control approachin cognitive radio systems based on spectrum sensing side information isimplemented to utilize the spectrum efficiently by allowing thecognitive radio to co-exist with the primary system. In accordance withvarious non-limiting embodiments of a method of the invention, thedistance d between the primary transmitter and the cognitive radio isdetermined based on spectrum sensing side information. Then, thetransmit power of the cognitive radio is controlled based on thedistance d in order to guarantee a QoS requirement of the primaryreceiver.

In order to avoid the harmful interference to the primary (licensed)system, a cognitive radio senses the availability of the spectrum via aprocess known as spectrum sensing. The goal of spectrum sensing is todecide between the following two hypotheses:H ₀ : x(t)=n(t) 0<t≦T(1)H ₁ : x(t)=hs(t)+n(t) 0<t≦T(2)  Eqn. 1where T denotes the observation time, x(t) is the received signal at thecognitive radio, s(t) is the transmitted signal from the primarytransmitter, n(t) is the zero-mean additive white Gaussian noise (AWGN)with the variance σ² and h denotes the Rayleigh fading channelcoefficient. The instantaneous SNR is defined as γ=|hs(t)|²/σ².

A challenge of spectrum sensing for cognitive radio is detecting thepresence of the primary transmitter with little information about thechannel h and the transmitted signal s(t). In such a scenario, theenergy detector has been shown as the optimal detector for a zero-meanconstellation of s(t). Specifically, the energy of the received signal,denoted by Y, is collected in a fixed bandwidth W and a time slotduration T and then compared with a pre-designed threshold λ. If Y>λ,then the cognitive radio assumes that the primary system is inoperation, i.e., H₁. Otherwise, it assumes H₀.

The average probability of false alarm, detection and missing of energydetection over Rayleigh fading channels can be given by, respectively,

$\begin{matrix}{{P_{f} = {{E_{\gamma}\left\lbrack {{Prob}\left\{ {H_{1}❘H_{0}} \right\}} \right\rbrack} = \frac{\Gamma\left( {u,\frac{\lambda}{2}} \right)}{\Gamma(u)}}},} & {{Eqn}.\mspace{14mu} 2} \\\begin{matrix}{P_{d} = {E_{\gamma}\left\lbrack {{Prob}\left\{ {H_{1}❘H_{1}} \right\}} \right\rbrack}} \\{= {{{\mathbb{e}}^{- \frac{\lambda}{2}}{\sum\limits_{n = 0}^{u - 2}{\frac{1}{n!}\left( \frac{\lambda}{2} \right)^{n}}}} + {\left( \frac{1 + \overset{\_}{\gamma}}{\overset{\_}{\gamma}} \right)^{u - 1} \times}}} \\{\left\lbrack {{\mathbb{e}}^{- \frac{\lambda}{2{({1 + \overset{\_}{\gamma}})}}} - {{\mathbb{e}}^{- \frac{\lambda}{2}}{\sum\limits_{n = 0}^{u - 2}{\frac{1}{n!}\left( \frac{\lambda\;\overset{\_}{\gamma}}{2\left( {1 + \overset{\_}{\gamma}} \right)} \right)^{n}}}}} \right\rbrack,\mspace{14mu}{and}}\end{matrix} & {{Eqn}.\mspace{14mu} 3} \\{{P_{m} = {{E_{\gamma}\left\lbrack {{Prob}\left\{ {H_{0}❘H_{1}} \right\}} \right\rbrack} = {1 - P_{d}}}},} & {{Eqn}.\mspace{14mu} 4}\end{matrix}$

where γ denotes the average SNR at the cognitive radio. E_(γ)[·]represents the expectation over the random variable γ which is Rayleighdistributed. Prob{·} stands for the probability. Γ(·,·) is theincomplete gamma function and Γ(·) is the gamma function. Finally, u=TWwith u=5 is used throughout this paper.

For each of curves 500, 510 and 520 of FIG. 5, P_(m) is plotted versusthe average SNR of the cognitive radio over Rayleigh fading under pathloss effects for P_(f)=0.1, 0.01 and 0.001, respectively. FIG. 5 showsthat when the average SNR increases, the probability of missing becomessmaller. For a specified average SNR, a larger P_(f) will result in thedecrease of P_(m) because of the decrease of the threshold used inenergy detection.

The path loss due to the distance d can be given by:

$\begin{matrix}{{\eta - {10\;{\log\left( d^{- \alpha} \right)}}},{{dB} = {{10\;{\log\left( \frac{Q_{p}}{\sigma^{2}} \right)}} - {10\;{\log\left( \overset{\_}{\gamma} \right)}}}},} & {{Eqn}.\mspace{14mu} 5}\end{matrix}$

where log(·) denotes the base-10 logarithm function. From Equation 5,the following equations are obtained:

$\begin{matrix}\begin{matrix}{\overset{\_}{\gamma} = {\frac{Q_{p}}{\sigma^{2}}d^{- \alpha}}} \\{= {\frac{Q_{p}/\sigma^{2}}{10^{\frac{\eta}{10}}}.}}\end{matrix} & {{Eqn}.\mspace{14mu} 6}\end{matrix}$

By substituting Equation 6 into Equation 3, a relationship between P_(m)and d (or η) for the given Q_(p)/σ² and α is obtained, as follows:P=f(d) or P _(m) =f(η).  Eqn. 7

The distance d (or η) can be decided by P_(m).

Each of curves 600, 610 and 620 of FIG. 6 shows P_(m) versus thedistance d for different transmit SNR Q_(p)/σ²=80,90 and 100,respectively, when α=2 and P_(f)=0.01. Numerical results demonstratethat when the cognitive radio is far from the primary transmitter, thereis a high probability of missing. For a fixed distance d, a highertransmit SNR can yield a better sensing performance, i.e., a lowerP_(m), because the received SNR γ is enhanced.

The miss detection occurs when the primary transmitter is in operation,but the cognitive radio fails to sense it. In this case, the probabilityof missing P_(m) can be calculated as follows. Let

$\begin{matrix}{{I\left( Y_{i} \right)} = \left\{ \begin{matrix}{1,} & {{{if}\mspace{14mu} Y_{i}} > {\lambda(10)}} \\{0,} & {{otherwise}(11)}\end{matrix} \right.} & {{Eqn}.\mspace{14mu} 8}\end{matrix}$for i=1, . . . , N, where Y_(i) denotes the energy collected by thecognitive radio in time slot i and N is the total number of time slots.Then, P_(m) can be estimated as

$\begin{matrix}{{\hat{P}}_{m} = {1 - {\frac{1}{N}{\sum\limits_{i = 1}^{N}{{I\left( Y_{i} \right)}.}}}}} & {{Eqn}.\mspace{14mu} 9}\end{matrix}$

Once P_(m) is determined, d (or η) can be obtained from Equation 7.

When the presence of the primary user is not properly detected duringthe spectrum sensing process, the overall system performance will bedegraded significantly due to the interference from the cognitive radio.Thus, in accordance with the invention, a transmit power control methodis proposed to address this problem by limiting the interference due tothe presence of the cognitive radio while also guaranteeing efficientspectrum utilization.

To allow the primary receiver to successfully decode the receivedsignals from the primary transmitter in the presence of the cognitiveradio, the signal-to-interference-plus-noise ratio (SINR) of the primaryreceiver should be guaranteed to be above a threshold of thedecodability SNR γ_(d) (in dB), i.e., SINR≧γ_(d). Then, the QoS for theprimary receiver can be evaluated by:

$\begin{matrix}{{\frac{Q_{p}}{Q_{c} + \sigma^{2}} \geq 10^{\frac{\gamma_{d}}{10}}},} & {{Eqn}.\mspace{14mu} 10}\end{matrix}$

where Q_(p) and Q_(c) denote the received signal power from the primarytransmitter and the cognitive radio, respectively. From Equation 10 andthe parameters shown in FIG. 2, the following equations are obtained:

$\begin{matrix}{{10\;{\log\left( \frac{Q_{c}}{\sigma^{2}} \right)}} \leq {\Delta + {10\;{\log\left( {10^{\frac{\mu}{10}} - 1} \right)}} + {10\;\alpha\;{\log\left( {\left( 10^{\frac{\psi}{10}} \right)^{\frac{1}{\alpha}} - \left( 10^{- \frac{\mu}{10}} \right)^{\frac{1}{\alpha}}} \right)}{g(\psi)}}}} & {{Eqn}.\mspace{14mu} 11}\end{matrix}$for the constants α and μ.

It can be seen from Equation 11 that the value of the allowable Q_(c)depends on the SNR loss ψ. Since the location of the primary receiver isusually unknown for the cognitive radio, it is difficult to get thevalue of ψ. In accordance with the invention, the worst case isconsidered where the primary receiver is located at the closest point tothe cognitive radio. In this case, from FIG. 4, the following equationpertains:ψ=η−Δ, dB.  Eqn. 12

By substituting Equation 12 into Equation 11, Q_(c) can be decided by η.Considering the case where η=−10 log(d^(−α)):

$\begin{matrix}\begin{matrix}{{Q_{c}^{\max} = {{g\left( {\eta - \Delta} \right)} + {10\;\log\left( \sigma^{2} \right)}}},{dB}} \\{{= {{g\left( {{{- 10}\;{\log\left( d^{- \alpha} \right)}} - \Delta} \right)} + {10\;{\log\left( \sigma^{2} \right)}}}},{dB}}\end{matrix} & {{Eqn}.\mspace{14mu} 13}\end{matrix}$

where Q_(c) ^(max) denote the maximum value of Q_(c) in dB and d hasbeen derived from the spectrum sensing side information above. As aresult, the transmit power of the cognitive radio that guaranteesacceptable QoS for the primary receiver is determined from the followingsteps for power control for cognitive radios in accordance withembodiments described herein:

Step 1: Calculate P_(m) from Equation 9.

Step 2: Derive d or η from Equation 7.

Step 3: Calculate Q_(c) ^(max) from Equation 13.

Some exemplary, non-limiting numerical results are presented tomathematically demonstrate the efficacy of the transmit power controlmethod in cognitive radio systems in accordance with the presentinvention, as described above.

These numerical results assume that the system parameters are asfollows:

-   -   Δ=60 dB;    -   μ=1 dB;    -   Q_(p)/σ²=100 dB;    -   P_(f)=0.01;    -   α=2.

Also, the channel environment is assumed to have flat Rayleigh fadingand path loss. In order to allow the cognitive radio to share thespectrum with the primary system while guaranteeing threshold QoS to theprimary receiver characterized by Equation 10, the transmit power of thecognitive radio should be controlled accordingly.

In the following, the efficacy of the invention is demonstrated byshowing that the maximum transmit power of the cognitive radio isobtained. Because it is difficult to locate the primary receiver for thecognitive radio, as mentioned above, the worst case scenario isconsidered where the primary receiver is the nearest to the cognitiveradio, as shown in FIG. 4.

From Equation 7, first, P_(m) vs. η (in dB) is obtained as shown bycurve 700 of FIG. 7, illustrating the proportional relationship betweenP_(m) and the SNR loss due to the distance d.

Then, from Equation 13, Q_(c) ^(max) vs. η (in dB) is obtained as shownby curve 800 of FIG. 8. Curve 800 of FIG. 8 demonstrates that theallowable transmit power of the cognitive radio can be increased when aheavy SNR loss occurs between the cognitive radio and the primaryreceiver. This is reasonable because the interference power that thecognitive radio inflicts on the primary receiver is reduced by the largepath loss.

Finally, from FIGS. 7 and 8, the relationship between Q_(c) ^(max) andP_(m) is established as illustrated by curve 900 of FIG. 9. Bycalculating P_(m) from Equation 9, the maximum transmit power Q_(c)^(max) can be determined to guarantee the QoS for the licensed user inthe presence of the cognitive radio. Because the maximum power of Q_(c)is evaluated according to the worse case scenario where the primaryreceiver is the nearest to the cognitive radio, the power controlapproach of the invention can be applied to a primary receiver in anylocation.

FIG. 10 is another flow diagram of an exemplary method for processingspectrum sensing side information to dynamically control transmit powerof a cognitive radio in a cognitive radio system in order tominimize/eliminate the possibility of interference by the cognitiveradio with the licensed users. At 1000, path loss of the channel betweenthe licensed user and the cognitive radio is derived based on thespectrum sensing side information. At 1010, the average probability ofmissing energy detection is calculated with respect to detectingtransmissions of the licensed user during spectrum sensing. At 1020, aset, or range, of candidate distances to the licensed user from thecognitive radio are derived based on spectrum sensing side information.Next, from the set or range of distance, the shortest distance of theset of candidate distances is selected at 1030. Then, at 1040, based onthe shortest distance to the licensed user (or shortest distances to thelicensed users where there are multiple licensed users), the transmitpower of the cognitive radio for transmissions in the shared spectrum isdynamically controlled to eliminate the possibility of interference withthe licensed user(s). Since the worst case is factored into thedetermination, even where the worst case manifests, the licensed userwill be able to continue without interference from the cognitive radiosin the shared spectrum.

The invention thus applies in the context of a primary user and acognitive radio sharing spectrum simultaneously. To limit theinterference to the primary user, a power control approach is providedin accordance with the invention which intelligently adjusts thetransmit power of the cognitive radio while maintaining a quality ofservice for the primary user. The transmit power is controlled by thespectrum sensing side information, the probability of missing whichactually includes the implicit location information of the primary user.Numerical results show that the invention guarantees a reliable qualityof service for the primary user in any location while greatly enhancingthe spectrum utilization.

Supplemental Context for Cognitive Radio Systems

Cognitive radio was conceived as an ideal goal towards which asoftware-defined radio platform should evolve: a fully reconfigurablewireless black box that automatically changes its communicationvariables in response to network and user demands.

With respect to the telecommunications industry, regulatory bodies invarious countries found that most of the radio frequency spectrum isutilized inefficiently. For instance, it was found that cellular networkbands are overloaded in most parts of the world, but amateur radio andpaging frequencies are not. Independent studies performed confirmed thatobservation and concluded that spectrum utilization depends strongly ontime and place. Moreover, fixed spectrum allocation prevents rarely usedfrequencies (those assigned to specific services) from being used byunlicensed users, even when their transmissions would not interfere atall with the assigned service. Accordingly, the rationale has developedfor allowing unlicensed users to utilize licensed bands whenever itwould not cause any interference (by avoiding them whenever thresholdlegitimate user presence is sensed).

Recently, for example, intense competition for spectrum usage hasarisen, especially for the spectrum below 3 GHz. Studies from theFederal Communication Commission (FCC) show that the utilization oflicensed spectrum only ranges from 15% to 85%. Aimed at making full useof the spectrum (white space), IEEE 802.22 Wireless Region Area Network(WRAN) Group is established to utilize the spectrum between 54 MHz and862 MHz. As a candidate for WRAN, cognitive radio techniques have beenpursued to exploit the existence of spectrum holes.

There are two main types of cognitive radio depending on the set ofparameters taken into account in deciding on transmission and receptionchanges: (1) full cognitive radio, or Mitola radio, in which everypossible parameter observable by a wireless node or network is takeninto account and (2) spectrum sensing cognitive radio in which only theradio frequency spectrum is considered. In addition, as anotherdistinguishing factor, with licensed band cognitive radio, bandsassigned to licensed users can be used apart from unlicensed bands. Withunlicensed band cognitive radio, only unlicensed parts of the radiofrequency spectrum are used.

Spectrum sensing cognitive radio has become of increasing interest tothe telecommunications industry. Applications of spectrum sensingcognitive radio include, but are by no means limited to, emergencynetworks and WLAN higher throughput and transmission distanceextensions. A focus of spectrum sensing cognitive radio is in designinghigh quality spectrum sensing devices and algorithms for exchangingspectrum sensing data between nodes.

In this regard, the main functions of cognitive radios are: (1) spectrumsensing, (2) spectrum management, (3) spectrum mobility and (4) spectrumsharing. Spectrum sensing by a cognitive radio involves detecting unusedspectrum and sharing it without harmful interference with other users.In this sense, a goal of cognitive radio networks is to sense spectrumholes, and one way to detect spectrum holes is to efficiently analyzeprimary users of the network.

Spectrum management involves capturing the best available spectrum tomeet user communication requirements, i.e., cognitive radios shoulddecide on the best spectrum band to meet any QoS requirements over allavailable spectrum bands involving spectrum analysis anddecision-making.

In turn, spectrum mobility is defined as the process when a cognitiveradio user exchanges its operative frequency. Cognitive radio networksaim to use spectrum dynamically by allowing radio terminals to operatein the best available frequency band, maintaining seamless communicationrequirements during the transition to better spectrum. As the nameimplies, spectrum sharing endeavors to provide a fair spectrumscheduling method for all nodes.

Exemplary Networked and Distributed Environments

One of ordinary skill in the art can appreciate that the variousembodiments of power control for cognitive radios described herein canbe implemented in connection with any computer or other client or serverdevice, which can be deployed as part of a computer network or in adistributed computing environment, and can be connected to any kind ofdata store. In this regard, the various embodiments described herein canbe implemented in any computer system or environment having any numberof memory or storage units, and any number of applications and processesoccurring across any number of storage units. This includes, but is notlimited to, an environment with server computers and client computersdeployed in a network environment or a distributed computingenvironment, having remote or local storage.

Distributed computing provides sharing of computer resources andservices by communicative exchange among computing devices and systems.These resources and services include the exchange of information, cachestorage and disk storage for objects, such as files. These resources andservices also include the sharing of processing power across multipleprocessing units for load balancing, expansion of resources,specialization of processing, and the like. Distributed computing takesadvantage of network connectivity, allowing clients to leverage theircollective power to benefit the entire enterprise. In this regard, avariety of devices may have applications, objects or resources that mayuse the power control for cognitive radios as described for variousembodiments of the subject disclosure.

FIG. 11 provides a schematic diagram of an exemplary networked ordistributed computing environment. The distributed computing environmentcomprises computing objects 1110, 1112, etc. and computing objects ordevices 1120, 1122, 1124, 1126, 1128, etc., which may include programs,methods, data stores, programmable logic, etc., as represented byapplications 1130, 1132, 1134, 1136, 1138. It can be appreciated thatobjects 1110, 1112, etc. and computing objects or devices 1120, 1122,1124, 1126, 1128, etc. may comprise different devices, such as PDAs,audio/video devices, mobile phones, MP3 players, personal computers,laptops, etc.

Each object 1110, 1112, etc. and computing objects or devices 1120,1122, 1124, 1126, 1128, etc. can communicate with one or more otherobjects 1110, 1112, etc. and computing objects or devices 1120, 1122,1124, 1126, 1128, etc. by way of the communications network 1140, eitherdirectly or indirectly. Even though illustrated as a single element inFIG. 11, network 1140 may comprise other computing objects and computingdevices that provide services to the system of FIG. 11, and/or mayrepresent multiple interconnected networks, which are not shown. Eachobject 1110, 1112, etc. or 1120, 1122, 1124, 1126, 1128, etc. can alsocontain an application, such as applications 1130, 1132, 1134, 1136,1138, that might make use of an API, or other object, software, firmwareand/or hardware, suitable for communication with or implementation ofthe power control for cognitive radios provided in accordance withvarious embodiments of the subject disclosure.

There are a variety of systems, components, and network configurationsthat support distributed computing environments. For example, computingsystems can be connected together by wired or wireless systems, by localnetworks or widely distributed networks. Currently, many networks arecoupled to the Internet, which provides an infrastructure for widelydistributed computing and encompasses many different networks, thoughany network infrastructure can be used for exemplary communications madeincident to the power control for cognitive radios as described invarious embodiments.

Thus, a host of network topologies and network infrastructures, such asclient/server, peer-to-peer, or hybrid architectures, can be utilized.In a client/server architecture, particularly a networked system, aclient is usually a computer that accesses shared network resourcesprovided by another computer, e.g., a server. In the illustration ofFIG. 11, as a non-limiting example, computers 1120, 1122, 1124, 1126,1128, etc. can be thought of as clients and computers 1110, 1112, etc.can be thought of as servers where servers 1110, 1112, etc. provide dataservices, such as receiving data from client computers 1120, 1122, 1124,1126, 1128, etc., storing of data, processing of data, transmitting datato client computers 1120, 1122, 1124, 1126, 1128, etc., although anycomputer can be considered a client, a server, or both, depending on thecircumstances. Any of these computing devices may be processing data, orrequesting services or tasks that may implicate the power control forcognitive radios as described herein for one or more embodiments.

A server is typically a remote computer system accessible over a remoteor local network, such as the Internet or wireless networkinfrastructures. The client process may be active in a first computersystem, and the server process may be active in a second computersystem, communicating with one another over a communications medium,thus providing distributed functionality and allowing multiple clientsto take advantage of the information-gathering capabilities of theserver. Any software objects utilized pursuant to the power control forcognitive radios can be provided standalone, or distributed acrossmultiple computing devices or objects.

In a network environment in which the communications network/bus 1140 isthe Internet, for example, the servers 1110, 1112, etc. can be Webservers with which the clients 1120, 1122, 1124, 1126, 1128, etc.communicate via any of a number of known protocols, such as thehypertext transfer protocol (HTTP). Servers 1110, 1112, etc. may alsoserve as clients 1120, 1122, 1124, 1126, 1128, etc., as may becharacteristic of a distributed computing environment.

Exemplary Computing Device

As mentioned, advantageously, the techniques described herein can beapplied to any device where it is desirable to have secondary users useunderutilized spectrum designated primarily for primary users. It shouldbe understood, therefore, that handheld, portable and other computingdevices and computing objects of all kinds are contemplated for use inconnection with the various embodiments, i.e., anywhere that a devicemay request a service in a cognitive radio network. Accordingly, thebelow general purpose remote computer described below in FIG. 12 is butone example of a computing device.

Although not required, embodiments can partly be implemented via anoperating system, for use by a developer of services for a device orobject, and/or included within application software that operates toperform one or more functional aspects of the various embodimentsdescribed herein. Software may be described in the general context ofcomputer-executable instructions, such as program modules, beingexecuted by one or more computers, such as client workstations, serversor other devices. Those skilled in the art will appreciate that computersystems have a variety of configurations and protocols that can be usedto communicate data, and thus, no particular configuration or protocolshould be considered limiting.

FIG. 12 thus illustrates an example of a suitable computing systemenvironment 1200 in which one or aspects of the embodiments describedherein can be implemented, although as made clear above, the computingsystem environment 1200 is only one example of a suitable computingenvironment and is not intended to suggest any limitation as to scope ofuse or functionality. Neither should the computing environment 1200 beinterpreted as having any dependency or requirement relating to any oneor combination of components illustrated in the exemplary operatingenvironment 1200.

With reference to FIG. 12, an exemplary device for implementing one ormore embodiments includes a general purpose computing device in the formof a computer 1210. Components of computer 1210 may include, but are notlimited to, a processing unit 1220, a system memory 1230, and a systembus 1222 that couples various system components including the systemmemory to the processing unit 1220.

Computer 1210 typically includes a variety of computer readable mediaand can be any available media that can be accessed by computer 1210.The system memory 1230 may include computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) and/orrandom access memory (RAM). By way of example, and not limitation,memory 1230 may also include an operating system, application programs,other program modules, and program data.

A user can enter commands and information into the computer 1210 throughinput devices 1240. A monitor or other type of display device is alsoconnected to the system bus 1222 via an interface, such as outputinterface 1250. In addition to a monitor, computers can also includeother peripheral output devices such as speakers and a printer, whichmay be connected through output interface 1250.

The computer 1210 may operate in a networked or distributed environmentusing logical connections to one or more other remote computers, such asremote computer 1270, via network interface 1260. The remote computer1270 may be a personal computer, a server, a router, a network PC, apeer device or other common network node, or any other remote mediaconsumption or transmission device, and may include any or all of theelements described above relative to the computer 1210. The logicalconnections depicted in FIG. 12 include a network 1272, such local areanetwork (LAN) or a wide area network (WAN), but may also include othernetworks/buses. Such networking environments are commonplace in homes,offices, enterprise-wide computer networks, intranets and the Internet.It will be appreciated that the network connections shown and describedare exemplary and other means of establishing a communications linkbetween the computers may be used.

Exemplary Communications Networks and Environments

The above-described optimization algorithms and processes may be appliedto any network, however, the following description sets forth someexemplary telephony radio networks and non-limiting operatingenvironments for communications made incident to the power controlalgorithms and processes of the present invention. The below-describedoperating environments should be considered non-exhaustive, however, andthus the below-described network architecture merely shows one networkarchitecture into which the present invention may be incorporated.

One can appreciate, however, that the invention may be incorporated intoany now existing or future alternative architectures for communicationnetworks as well.

The global system for mobile communication (“GSM”) is one of the mostwidely utilized wireless access systems in today's fast growingcommunication systems. GSM provides circuit-switched data services tosubscribers, such as mobile telephone or computer users. General PacketRadio Service (“GPRS”), which is an extension to GSM technology,introduces packet switching to GSM networks. GPRS uses a packet-basedwireless communication technology to transfer high and low speed dataand signaling in an efficient manner. GPRS optimizes the use of networkand radio resources, thus enabling the cost effective and efficient useof GSM network resources for packet mode applications.

As one of ordinary skill in the art can appreciate, the exemplaryGSM/GPRS environment and services described herein can also be extendedto 3G services, such as Universal Mobile Telephone System (“UMTS”),Frequency Division Duplexing (“FDD”) and Time Division Duplexing(“TDD”), High Speed Packet Data Access (“HSPDA”), cdma2000 1× EvolutionData Optimized (“EVDO”), Code Division Multiple Access-2000 (“cdma20003×”), Time Division Synchronous Code Division Multiple Access(“TD-SCDMA”), Wideband Code Division Multiple Access (“WCDMA”), EnhancedData GSM Environment (“EDGE”), International MobileTelecommunications-2000 (“IMT-2000”), Digital Enhanced CordlessTelecommunications (“DECT”), etc., as well as to other network servicesthat shall become available in time. In this regard, the techniques ofthe invention may be applied independently of the method of datatransport, and does not depend on any particular network architecture,or underlying protocols.

FIG. 13 depicts an overall block diagram of an exemplary packet-basedmobile cellular network environment, such as a GPRS network, in whichthe invention may be practiced. In such an environment, there are aplurality of Base Station Subsystems (“BSS”) 1300 (only one is shown),each of which comprises a Base Station Controller (“BSC”) 1302 serving aplurality of Base Transceiver Stations (“BTS”) such as BTSs 1304, 1306,and 1308. BTSs 1304, 1306, 1308, etc. are the access points where usersof packet-based mobile devices become connected to the wireless network.In exemplary fashion, the packet traffic originating from user devicesis transported over the air interface to a BTS 1308, and from the BTS1308 to the BSC 1302.

Base station subsystems, such as BSS 1300, are a part of internal framerelay network 1310 that may include Service GPRS Support Nodes (“SGSN”)such as SGSN 1312 and 1314. Each SGSN is in turn connected to aninternal packet network 1320 through which a SGSN 1312, 1314, etc. canroute data packets to and from a plurality of gateway GPRS support nodes(GGSN) 1322, 1324, 1326, etc. As illustrated, SGSN 1314 and GGSNs 1322,1324, and 1326 are part of internal packet network 1320. Gateway GPRSserving nodes 1322, 1324 and 1326 mainly provide an interface toexternal Internet Protocol (“IP”) networks such as Public Land MobileNetwork (“PLMN”) 1345, corporate intranets 1340, or Fixed-End System(“FES”) or the public Internet 1330. As illustrated, subscribercorporate network 1340 may be connected to GGSN 1324 via firewall 1332;and PLMN 1345 is connected to GGSN 1324 via boarder gateway router 1334.The Remote Authentication Dial-In User Service (“RADIUS”) server 1342may be used for caller authentication when a user of a mobile cellulardevice calls corporate network 1340.

Generally, there can be four different cell sizes in a GSMnetwork—macro, micro, pico and umbrella cells. The coverage area of eachcell is different in different environments. Macro cells can be regardedas cells where the base station antenna is installed in a mast or abuilding above average roof top level. Micro cells are cells whoseantenna height is under average roof top level; they are typically usedin urban areas. Pico cells are small cells having a diameter is a fewdozen meters; they are mainly used indoors. On the other hand, umbrellacells are used to cover shadowed regions of smaller cells and fill ingaps in coverage between those cells.

Thus, network elements that may implicate the functionality of theoptimization algorithms and processes in accordance with the inventionmay include but are not limited to Gateway GPRS Support Node tables,Fixed End System router tables, firewall systems, VPN tunnels, and anynumber of other network elements as may be required by a given network.

As mentioned above, while exemplary embodiments have been described inconnection with various computing devices and network architectures, theunderlying concepts may be applied to any network system and anycomputing device or system in which it is desirable to performcooperative spectrum sensing in a cognitive radio network.

Also, there are multiple ways to implement the same or similarfunctionality, e.g., an appropriate API, tool kit, driver code,operating system, control, standalone or downloadable software object,etc. which enables applications and services to request network spectrumin a cognitive radio network according to the embodiments herein. Thus,the above described embodiments are contemplated from the standpoint ofan API (or other software object), as well as from a software orhardware object that provides any of the various capabilities describedabove. Moreover, various embodiments described herein can have aspectsthat are wholly in hardware, partly in hardware and partly in software,as well as in software.

While the present invention has been described in connection with thepreferred embodiments of the various figures, it is to be understoodthat other similar embodiments may be used or modifications andadditions may be made to the described embodiment for performing thesame function of the present invention without deviating therefrom. Forexample, one skilled in the art will recognize that the presentinvention as described in the present application may apply to anyenvironment, whether wired or wireless, and may be applied to any numberof such devices connected via a communications network and interactingacross the network. Therefore, the present invention should not belimited to any single embodiment, but rather should be construed inbreadth and scope in accordance with the appended claims.

The word “exemplary” is used herein to mean serving as an example,instance, or illustration. For the avoidance of doubt, the subjectmatter disclosed herein is not limited by such examples. In addition,any aspect or design described herein as “exemplary” is not necessarilyto be construed as preferred or advantageous over other aspects ordesigns, nor is it meant to preclude equivalent exemplary structures andtechniques known to those of ordinary skill in the art. Furthermore, tothe extent that the terms “includes,” “has,” “contains,” and othersimilar words are used in either the detailed description or the claims,for the avoidance of doubt, such terms are intended to be inclusive in amanner similar to the term “comprising” as an open transition wordwithout precluding any additional or other elements.

Various implementations of the invention described herein may haveaspects that are wholly in hardware, partly in hardware and partly insoftware, as well as in software. As used herein, the terms “component,”“system” and the like are likewise intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon computer and the computer can be a component. One or more componentsmay reside within a process and/or thread of execution and a componentmay be localized on one computer and/or distributed between two or morecomputers.

Thus, the methods and apparatus of the present invention, or certainaspects or portions thereof, may take the form of program code (i.e.,instructions) embodied in tangible media, such as floppy diskettes,CD-ROMs, hard drives, or any other machine-readable storage medium,wherein, when the program code is loaded into and executed by a machine,such as a computer, the machine becomes an apparatus for practicing theinvention. In the case of program code execution on programmablecomputers, the computing device generally includes a processor, astorage medium readable by the processor (including volatile andnon-volatile memory and/or storage elements), at least one input device,and at least one output device.

Furthermore, the disclosed subject matter may be implemented as asystem, method, apparatus, or article of manufacture using standardprogramming and/or engineering techniques to produce software, firmware,hardware, or any combination thereof to control a computer or processorbased device to implement aspects detailed herein. The terms “article ofmanufacture”, “computer program product” or similar terms, where usedherein, are intended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. For example, computerreadable media can include but are not limited to magnetic storagedevices (e.g., hard disk, floppy disk, magnetic strips . . . ), opticaldisks (e.g., compact disk (CD), digital versatile disk (DVD) . . . ),smart cards, and flash memory devices (e.g., card, stick). Additionally,it is known that a carrier wave can be employed to carrycomputer-readable electronic data such as those used in transmitting andreceiving electronic mail or in accessing a network such as the Internetor a local area network (LAN).

The aforementioned systems have been described with respect tointeraction between several components. It can be appreciated that suchsystems and components can include those components or specifiedsub-components, some of the specified components or sub-components,and/or additional components, and according to various permutations andcombinations of the foregoing. Sub-components can also be implemented ascomponents communicatively coupled to other components rather thanincluded within parent components, e.g., according to a hierarchicalarrangement. Additionally, it should be noted that one or morecomponents may be combined into a single component providing aggregatefunctionality or divided into several separate sub-components, and anyone or more middle layers, such as a management layer, may be providedto communicatively couple to such sub-components in order to provideintegrated functionality. Any components described herein may alsointeract with one or more other components not specifically describedherein but generally known by those of skill in the art.

In view of the exemplary systems described supra, methodologies that maybe implemented in accordance with the disclosed subject matter will bebetter appreciated with reference to the flowcharts of the variousfigures. While for purposes of simplicity of explanation, themethodologies are shown and described as a series of blocks, it is to beunderstood and appreciated that the claimed subject matter is notlimited by the order of the blocks, as some blocks may occur indifferent orders and/or concurrently with other blocks from what isdepicted and described herein. Where non-sequential, or branched, flowis illustrated via flowchart, it can be appreciated that various otherbranches, flow paths, and orders of the blocks, may be implemented whichachieve the same or a similar result. Moreover, not all illustratedblocks may be required to implement the methodologies describedhereinafter.

Furthermore, as will be appreciated various portions of the disclosedsystems above and methods below may include or consist of artificialintelligence or knowledge or rule based components, sub-components,processes, means, methodologies, or mechanisms (e.g., support vectormachines, neural networks, expert systems, Bayesian belief networks,fuzzy logic, data fusion engines, classifiers . . . ). Such components,inter alia, can automate certain mechanisms or processes performedthereby to make portions of the systems and methods more adaptive aswell as efficient and intelligent.

While the present invention has been described in connection with thepreferred embodiments of the various figures, it is to be understoodthat other similar embodiments may be used or modifications andadditions may be made to the described embodiment for performing thesame function of the present invention without deviating therefrom.

While exemplary embodiments refer to utilizing the present invention inthe context of particular programming language constructs,specifications or standards, the invention is not so limited, but rathermay be implemented in any language to enable the power controlalgorithms for cognitive radios as described herein. Still further, thepresent invention may be implemented in or across a plurality ofprocessing chips or devices, and storage may similarly be effectedacross a plurality of devices. Therefore, the present invention shouldnot be limited to any single embodiment, but rather should be construedin breadth and scope in accordance with the appended claims.

What is claimed is:
 1. A method, comprising: determining, by a computingdevice including a processor, an average probability of a missing energydetection of a primary transmitter of a primary device based on sensinginformation associated with a cognitive radio device; and determining,by the computing device, a distance parameter between the primarytransmitter and the cognitive radio device based upon the averageprobability of the missing energy detection.
 2. The method of claim 1,further comprising: controlling, by the computing device, a transmitpower of the cognitive radio device based on the distance parameter tomeet a quality of service requirement for the primary device.
 3. Themethod of claim 2, wherein the controlling the transmit power comprises:determining a maximum transmit power that meets the quality of servicerequirement based upon a path loss function of the distance parameter;and limiting the transmit power to the maximum transmit power.
 4. Themethod of claim 1, wherein the determining the distance parametercomprises: determining a plurality of candidate distances between theprimary transmitter and the cognitive radio device based upon theaverage probability of the missing energy detection; and setting thedistance parameter to a shortest distance of the plurality of candidatedistances.
 5. The method of claim 1, further comprising: determining, bythe computing device, the sensing information by monitoring energy of asignal received by the cognitive radio device in a predeterminedbandwidth for predetermined period of time.
 6. A cognitive radio device,comprising: a spectrum sensing component configured to: estimate anaverage probability of a missing energy detection of a primarytransmitter of a primary device based on sensing information associatedwith a cognitive radio device; and estimate a distance parameter betweenthe primary transmitter and the cognitive radio device based upon theaverage probability of the missing energy detection.
 7. The cognitiveradio device of claim 6, further comprising: a power control componentconfigured to adjust a transmit power of the cognitive radio devicebased on the distance parameter to meet a quality of service requirementfor the primary device.
 8. The cognitive radio device of claim 7,wherein the power control component is further configured to: determinea maximum transmit power that meets the quality of service requirementbased upon a path loss function of the distance parameter; and preventthe transmit power from exceeding the maximum transmit power.
 9. Thecognitive radio device of claim 6, wherein the spectrum sensingcomponent is further configured to: identify a plurality of candidatedistances between the primary transmitter and the cognitive radio devicebased upon the average probability of the missing energy detection; andset the distance parameter to a shortest distance of the plurality ofcandidate distances.
 10. The cognitive radio device of claim 6, whereinthe spectrum sensing component is further configured to determine thesensing information by monitoring energy of a signal received by thecognitive radio device in a predetermined spectrum for at least onepredetermined time slot.
 11. A non-transitory computer readable storagemedium comprising computer executable instructions that, in response toexecution, cause a device including a processor to perform operations,comprising: approximating an average probability of a missing energydetection of a primary transmitter of a primary device based on sensinginformation associated with a cognitive radio device; and identifying adistance parameter between the primary transmitter and the cognitiveradio device based upon the average probability of the missing energydetection.
 12. The non-transitory computer readable storage medium ofclaim 11, wherein the operations further comprise modifying a transmitpower of the cognitive radio device based on the distance parameter tomeet a quality of service requirement for the primary device.
 13. Thenon-transitory computer readable storage medium of claim 12, wherein theoperations further comprise: identifying a maximum transmit power thatmeets the quality of service requirement based upon a path loss functionof the distance parameter; and inhibiting the transmit power fromexceeding the maximum transmit power.
 14. The non-transitory computerreadable storage medium of claim 11, wherein the identifying thedistance parameter comprises: estimating a plurality of candidatedistances between the primary transmitter and the cognitive radio devicebased upon the average probability of the missing energy detection; andselecting a distance as a function of a shortest distance of theplurality of candidate distances as the distance parameter.
 15. Thenon-transitory computer readable storage medium of claim 11, wherein theoperations further comprise obtaining the sensing information bymonitoring energy of a signal received by the cognitive radio device ina predetermined bandwidth for one or more predetermined time intervals.16. A system, comprising: means for calculating an average probabilityof a missing energy detection of a primary transmitter of a primarydevice based on sensing information associated with a cognitive radiodevice; and means for determining a distance parameter between theprimary transmitter and the cognitive radio device based upon theaverage probability of the missing energy detection.
 17. The system ofclaim 16, further comprising: means for setting a transmit power of thecognitive radio device based on the distance parameter to meet a qualityof service requirement for the primary device.
 18. The system of claim17, further comprising: means for determining a maximum transmit powerthat meets the quality of service requirement based upon a path lossfunction of the distance parameter; and means for blocking the transmitpower from exceeding the maximum transmit power.
 19. The system of claim16, wherein the means for determining the distance parameter comprises:means for identifying a plurality of candidate distances between theprimary transmitter and the cognitive radio device based upon theaverage probability of the missing energy detection; and means forsetting the distance parameter to a shortest distance of the pluralityof candidate distances.
 20. The system of claim 16, further comprising:means for determining the sensing information by monitoring energy of asignal received by the cognitive radio device in at least onepredetermined spectrum for at least one predetermined time period.